Tarzana Crime Rate Trends — Los Angeles
Tarzana is a southern San Fernando Valley neighborhood organized around Ventura Boulevard, named for Edgar Rice Burroughs's Tarzana ranch. Predominantly single-family ranch homes south of Ventura on the Santa Monica Mountains foothills.
Four signals moved in Tarzana in March 2026 — one spike, one single-month drop, and two sustained shifts. The shape is mixed: property crime is broadly lower on a 12-month basis, but other larceny is running sharply above its prior-year level, pulling against the otherwise downward pattern.
Other larceny is the most prominent signal: 399 incidents in the current 12 months against 204 in the prior year, a 61.5% increase and well above the 204.27 baseline mean. Theft from vehicle moved in the opposite direction — down 25.1% year-over-year (143 vs. 191) — and registered both a single-month below-trend signal and a sustained structural shift, meaning the decline has been accumulating over multiple months. Burglary also continued lower at -22.1%, and robbery fell 16.7% to 40 incidents from 48.
Notable signals 2
Other Larceny
The past 12 months saw 399 incidents — about 95% above the 204 average from prior years.
Theft from Vehicle
The past 12 months saw 143 incidents — about 41% below the 244 average from prior years.
All categories, last 24 months
Each panel: recent monthly count vs. trailing 12-month context. MoM is the most recent month vs. the one before; 12mo YoY compares the trailing year to the year before that.
What's been quietly true for a year
Spikes get attention. Sustained shifts shape policy. These are multi-quarter patterns where the past 12-month total differs meaningfully from the year before — they often precede the baseline resetting.
- Other Larceny is climbing.
The trailing 12-month count is 399, up 62% from 247 the year before. If the trend holds another quarter, it will pull the multi-year baseline up.
- Theft from Vehicle has reset to a lower baseline.
The trailing 12-month count is 143, down 25% from 191 the year before. If the trend holds another quarter, it will pull the multi-year baseline down.
What next month likely looks like
Forecasts trained through March 2026, with a likely range we're 95% confident the actual count will fall inside. Categories with too little recent volume — or violent categories at the neighborhood level — show no forecast and are surfaced through signals above instead. See the methodology page for the gating rules.
Aggravated Assault
Too low-volume per neighborhood for a reliable point forecast — see the rare-event and streak-break signals above instead.
Arson
Below the volume threshold for a reliable forecast — too few incidents in recent months to project from.
Burglary
Homicide
Too low-volume per neighborhood for a reliable point forecast — see the rare-event and streak-break signals above instead.
Motor Vehicle Theft
Other Larceny
Robbery
Too low-volume per neighborhood for a reliable point forecast — see the rare-event and streak-break signals above instead.
Sexual Assault
Too low-volume per neighborhood for a reliable point forecast — see the rare-event and streak-break signals above instead.
Theft from Vehicle
Vandalism
How Tarzana compares
Peer neighborhoods picked by closest 12-month other larceny volume — a pragmatic v1 of peer matching. Demographic / housing-stock peer matching isn't built yet (we deliberately don't ingest income or race data alongside crime). Volume similarity has the right intuition: “neighborhoods experiencing comparable other larceny levels.”
Mid-Wilshire
395 incidents over the past 12 months — 4 below Tarzana's 399.
Open page →Encino
414 incidents over the past 12 months — 15 above Tarzana's 399.
Open page →Westlake
378 incidents over the past 12 months — 21 below Tarzana's 399.
Open page →Recurring local terms (last 12 months)
Top terms in incident descriptions for Tarzana, excluding generic crime taxonomy. Useful as texture — what kinds of specifics show up here that don't show up elsewhere.
Hour-of-day, day-of-week, and seasonality
Distribution of bucketed incidents in this neighborhood across the full analysis window. Useful for routine context — shopping-strip thefts vs. late-night assaults read very differently when you can see when each typically happens.
How we built this page
Data → Anomalies → Forecast → Page
Incident data is pulled from SFPD's open dataset, mapped to 10 NIBRS-aligned categories, and aggregated to neighborhood × category × month. Anomalies are surfaced using strict thresholds (~p < 0.01). Forecasts are Prophet with low-count gating; violent categories at the neighborhood level skip the forecast and show rare-event / streak signals instead.
Spike rule: 12-mo total > baseline mean + 2.5σ AND ≥ 20 incidents AND 6-mo confirms. Drop rule: 12-mo total < baseline mean − 2.5σ AND baseline mean ≥ 20. Rare event: any incident in the last 90 days, no prior comparable in ≥ 5 years.